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Five (5) years of experience must include: Informatica AXON; EDC; IDQ; Collibra; Implementing Data Quality frameworks, metadata management solution and data governance solutions; AWS, big data technologies, python and databases; Overseeing projects and programs with a focus on delivery; Data management; Data Governance strategy; Presentation Skills; Software Design and Architecture; Project/Program Management; Stakeholder Management.
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Data Strategy: Requires knowledge of understanding of business value and relevance of data and data enabled insights / decisions; Appropriate application and understanding of data ecosystem including Data Management, Data Quality Standards and Data Governance, Accessibility, Storage and Scalability etc; Understanding of the methods and applications that unlock the monetary value of data assets.
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Data governance best practices are implemented to manage data domain, data integration, data quality, and data access. Experience with Google Big Query, AWS databases, Oracle SQL, mySQL, PostgreSQL, and other data technologies.
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Experience with more than one data cataloguing, data governance, data quality, data privacy and master data management (Informatica, Ataccama, Collibra, Alation, Global Ids, Big Id, etc.
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Enterprise Data Management: Proficiency in data management strategies including data governance, data quality, and master data management. As a Senior Data Architect specializing in Data Discovery, Data Mapping, Data Modeling, Data Quality, Enterprise Information Model adoption, different types of Database Storage Systems involving relational, NoSQL, azure cloud data solutions, and Big Data Analytical Platforms, you will play a pivotal role in designing, implementing, and optimizing our data architecture artifacts to support advanced data initiatives.
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Data Modeling: Requires knowledge of cloud data strategy, data warehouse, data lake, and enterprise big data platforms; Data modeling techniques and tools (For example, Dimensional design and scalability), Entity Relationship diagrams, Erwin, etc; Query languages SQL / NoSQL; Data flows through the different systems; Tools supporting automated data loads; Artificial Intelligent - enabled metadata management tools and techniques.
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Guide the formulation of information development and data governance initiatives by defining data quality standards, metadata management practices, and data lineage tracking mechanisms.
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This includes managing data lakes, data warehouses, and databases, as well as implementing best practices for data modeling, data quality, and data governance.
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Master Data Management / Data Quality Management / Governance Collibra, Atacama, Alation, Reltio etc. Job Schedulers – Airflow, Oozie or other ETL Scheduler Data Analytics – AWS Cloud Native Services Big data architecture – Python, Scala, Hadoop Bigdata, Hive, Pyspark etc.
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Cross-functional knowledge of common enterprise data concepts: modern data stack, data engineering, data governance, data quality, master data management, and advanced analytics.
$185,000 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Provide guidance to business stakeholders, peers, and junior associates on the implementation of data governance practices. Tech. Problem Formulation: Requires knowledge of analytics/big data analytics / automation techniques and methods; Business understanding; Precedence and use cases; Business requirements and insights.
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Data Governance Knowledge Skills Understanding of data governance frameworks, policies, data cataloging, CDE, metadata and data quality Ability to implement and enforce data governance standards.
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Enterprise-wide Data Governance: Lead and establish robust enterprise-wide data governance practices, ensuring data quality, security, and compliance. Strong experience working on Databricks, DBT and data visualization tools like Power BI Strong knowledge of database technologies, ETL processes, cloud platforms, and big data technologies.
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Develop and maintain data management and governance standards, policies, and best practices, including metadata management, data quality management, master data management, data lineage, and other related areas.
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Data Management : Proficiency in data management strategies including data governance, data quality, and master data management. Implement data governance policies and standards to ensure data quality, security, and compliances.
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